llm-quality

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

一部由 AI Agent 独立生成的 78 万字网络小说，本项目的核心目的是通过一个真实的长程任务，展示当前顶级大语言模型的问题：碎片化水文、叙事模板化、剧情推进缓慢等。A 780K-character web novel generated independently by an AI Agent. This project's core purpose is to demonstrate the problems of current top-tier llm through a real long-form task: fragmented padding, formulaic narrative, slow plot progression, and more.

Open Council: Claude Code skill for multi-agent AI quality control. Ten specialist employees draft the work. Ten industry-veteran board members review it. You see one verdict. Anti-sycophancy, anti-hallucination, multi-perspective review.

AI 实用 Skill 库 · 16 ready-to-use Codex/Claude Agent skills: job-search memory, offer decision, LLM output quality gate, portfolio publishing, headless webapp screenshots, Remotion QA, vibecoding resume, Anna app publishing, static-site deploy verify, multi-machine memory sync. Zero dependency, privacy-safe.

Evidence-based evaluation of 27 real-world ChatGPT Go cases, covering instruction following, context handling, reasoning, tool use, and LLM response quality.